1. Field of the Invention
The present invention relates to data warehousing, and more particularly to performing dimensional modeling on data received in technology such as customer relationship management system environments.
2. Description of the Related Art
Many different kinds of computer hardware and software applications are used to support sales operations. For example, customer relationship management (“CRM”) and sales force automation (“SFA”) applications have evolved into complex data management mechanisms. CRM systems typically receive data collected from a plurality of sources, i.e., interactions with sales contacts and data from marketing services. The data are, typically, stored in a transactional database for future analysis and manipulation. SFA, typically, refers to software that operates in conjunction with CRM systems, and provides personal information management (“PIM”) functionality (e.g., software to manage appointments, contacts, notes and the like).
Sales representatives in the field use CRM and SFA applications to support their sales efforts. As used herein “CRM/SFA” refers to either a CRM system, an SFA system, or both.
The rapid adoption of next generation CRM/SFA systems in the pharmaceutical industry has focused largely on selecting appropriate computer hardware and software platforms. One of the goals of a CRM/SFA system is to make sales representatives more effective at driving market share for the products they are promoting. The ability to meet sales quotas and generate income, as well as to contribute to a product gaining market share, reflects a sales representative's performance. Typically, sales operations managers focus on system implementation issues and pay less attention to understanding what factors drive sales representative performance. Even less attention is paid to understanding how to adjust the CRM/SFA environment to optimize sales representative performance. This is largely due to the complexity of the CRM/SFA environment, and the variety of measurable and immeasurable factors that comprise sales representative success.
The effectiveness of a CRM/SFA environment depends on a plurality of interrelated services, for example, CRM/SFA help desk support, hardware service support, asset management, applications administration and maintenance, database administration and data production. No system currently exists that aggregates data from these sources in order to measure the effectiveness of CRM/SFA systems.
Typically, sales representatives in the field use portable computing devices, such as laptop computers, notebook computers and personal digital assistant devices (e.g., POCKETPC, WINDOWS CE and PALM computing devices) to operate CRM/SFA systems. A sales representative has CRM/SFA software installed on the device(s), for example, to manage the sales representative's sales contacts, schedule sales calls and provide data related to a single sales call. Sales representatives are trained in the hardware and software platforms they use, and, thereafter, use their technical skills to prepare for sales calls, enter information regarding sales calls, and otherwise use the technology. Typically, the data are uploaded regularly to another device, such as a data server that supports data transmissions from many sales representatives. Known in the art as “synchronizing” (or “synching”), data are transmitted and stored in a transactional database server for future analysis in customer relationship management, manipulation and archiving.
The training of sales representatives in CRM/SFA systems is an ongoing process. Components of CRM/SFA systems are often underutilized or ignored, thereby prompting sales representatives to undergo training in the technology. Also, training is provided when new technology is introduced or changes to existing technology occur. Further, hardware and software technical support services are provided to assist sales representatives in the field. Such support is, typically, in the form of telephone “help-desk” support, but can also be provided over the Internet via one or more web pages. Information generated by technical training and support services is usually stored on separate and disparate systems from the transactional database server receiving data during synchronization, and, therefore, cannot be readily analyzed.
One vendor of CRM/SFA software applications is SIEBEL SYSTEMS, INC. (hereinafter, “SIEBEL”). SIEBEL currently provides a suite of products directed to CRM/SFA systems, including transactional and analytical software. Data received from transactional software refer to information collected by a sales representative in the field and directed to sales contacts, sales calls and the like. These data are stored in an on-line transactional database, or OLTP. Alternatively, on-line analytical processing (“OLAP”) systems store the data and present the information in useful ways. With respect to the pharmaceutical industry, SIEBEL currently provides SIEBEL PHARMA, a software application that includes a suite of products including support for sales, customer service and marketing for the pharmaceutical industry.
Other software systems are known that provide analysis on data received from various sources. One system, provided by SAS and entitled ANALYTIC INTELLIGENCE, enables users to perform statistical analysis (e.g., linear regression) to generate information that provides insight into various business practices. Predictive modeling, forecasting, simulation, and optimization are also provided by SAS ANALYTIC INTELLIGENCE (see, for example, http://www.sas.com/technologies/analytics/). SIEBEL also currently provides data analysis software, SIEBEL ANALYTICS. This software platform provides analysis and warehousing for transactional data received from a transactional source system. SIEBEL ANALYTICS provides information which, in addition to the transactional data received from sales representatives in the field, is warehoused in a large database, such as provided by ORACLE CORPORATION. The data warehouse facilitates presentation of the data in graphical and contextual views.
Other software systems are known that provide the ability to extract, transform and load data from one system (typically the OLTP system) to the OLAP system. One system, provided by INFORMATICA, leverages, integrates, and transforms enterprise data from any source into the OLAP system. Of course, one skilled in the art will recognize that the extraction, transformation and loading (“ETL”) process requires significant customization to ensure the data are correctly transferred and the applicable business rules are applied.
One skilled in the art will recognize that other CRM/SFA systems exist. In the pharmaceutical industry, for example, DENDRITE, STAYINFRONT, and CEGEDIM provide CRM/SFA solutions for sales forces. Also, COGNOS, MICROSTRATEGY, and BRIO SOFTWARE are examples of companies and software that provide analytical and presentation packages for data warehousing. With respect to the pharmaceutical industry, SIEBEL is a leading market share provider of CRM/SFA systems, and, accordingly, is used in many of the examples provided herein.
While the adoption of CRM/SFA systems is assumed to have led to improvements in sales representative performance, studies have shown that technology has not necessarily positively impacted performance (see “Productivity Paradox” theory as outlined in “U.S. Productivity Growth 1995-2000” by Bill Lewis, McKinsey Global Institute.) Much of the data that are provided in CRM/SFA systems are not analyzed sufficiently to lead to such improvements in productivity and effectiveness. Moreover, information from a plurality of sources, for example, learning management systems, training, support and customer surveys are not adequately aggregated and analyzed in order to explore strategies that lead to improvements. For example, learning management systems comprise on-line and classroom teaching for employees, management and the like. The support environment includes technical support (telephone, on-line and/or in person) for hardware and software applications. Further, data gathered in surveys can provide insights into the benefit technology provides with respect to sales representative performance. Unfortunately, information generated in learning management systems, technical support systems and customer feedback modules are, typically, stored in disparate and separate systems. Other information, including demographic data, attainment of quota data, sales call data, number of details data and the like can also contribute to measuring the benefits of technology with respect to sales representative performance, but are also, typically, stored in separate and disparate systems. Therefore, end-user productivity does not measurably improve by analyzing the data from these respective sources in isolation from each other.
As CRM/SFA systems are deployed and implemented, issues invariably arise from a need to explore the effects of the systems on sales force efficiency. Examples of such issues include which parties are using the system, how the system is being used, how the system drives field behavior, whether the system needs improvement (and if so, where), and what elements of the system are misunderstood, thereby requiring additional training for the sales force. In the prior art, answers to these questions are not readily available because systems do not exist that aggregate and analyze information received from the CRM/SFA system, learning management systems, support environments and customer surveys. Therefore, upper management are left wondering of the degree they are receiving benefit for the substantial investment in a CRM/SFA system, and whether the CRM/SFA system drives sales and/or improves the bottom line.
Although significant amounts of data are gathered in prior art CRM/SFA systems, management remains concerned about whether field representatives use CRM/SFA systems effectively; for example, whether actual usage of the systems reflects intended usage. In prior art, data warehousing systems built from CRM/SFA data enabled management to monitor usage based on logon or frequency of synchs. Data based on these sources may provide a proxy for CRM/SFA usage, but do not provide sufficient detail of how a system is being used. Moreover, the impact of CRM/SFA systems on sales representative performance can not be determined satisfactorily using prior art CRM/SFA systems.
Referring to the drawing figures, in which like reference numerals refer to like elements, there is shown in FIG. 1 a representation of a typical distribution of sales force performance. As shown in FIG. 1, a distribution of sales representatives indicates a top twenty percent tier who achieve their goals consistently. Sixty percent of the sales force comprise the middle tier, and represent those who do not achieve performance goals to the extent of the top twenty percent tier. Twenty percent of the sales force are in the bottom tier and achieve below the performance goals of the middle tier. Despite the deployment of CRM /SFA systems, the distribution of sales force performance remains as represented in FIG. 1.
In a typical pharmaceutical sales force, each sales representative is exclusively assigned to a specific sales territory that includes sales contacts (i.e., doctors and other health care providers). A plurality of sales territories comprise a sales district. A plurality of sales districts comprise a sales region. A sales representative is assigned to a sales territory and that representative's sales performance is measured at least in terms of the performance of other sales representatives operating in the same sales district.
Ideally, each sales representative is offered equal access to a number of sales contacts who are receptive to meeting with a sales representative and a number of contacts who are less so. The sales territories are defined such that each sales representative has an equal chance of reaching receptive (and less receptive) contacts, thereby enabling each sales representative to meet his/her sales quota requirements. In the pharmaceutical industry, for example, no single sales representative has unrestricted access to the same group of physicians who are generally receptive to sales representatives, while other sales representatives are forced to engage physicians who are unresponsive to sales representatives, in general.